Journal
COMPUTING IN SCIENCE & ENGINEERING
Volume 16, Issue 4, Pages 41-52Publisher
IEEE COMPUTER SOC
DOI: 10.1109/MCSE.2014.52
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Big Data, a large and complex collection of datasets characterized by four V's (volume, variety, veracity, and velocity), is difficult to deal with using traditional data processing algorithms and models. A proposed dictionary learning algorithm, which extends the classical method that uses the K-means and Singular Value Decomposition (K-SVD) algorithm by incrementally, updating atoms, will ably represent the spatiotemporal remote sensing of Big Data and do so both efficiently and sparsely.
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